Measurement of Electrochemical Machining Initial Gap Based on Machine Vision

2011 ◽  
Vol 230-232 ◽  
pp. 1190-1194 ◽  
Author(s):  
Min Kang ◽  
Hou Shang Li ◽  
Xiu Qing Fu
Keyword(s):  
Machine Vision ◽  
Measurement System ◽  
Measurement Method ◽  
Electrochemical Machining ◽  
Image Data ◽  
Ccd Camera ◽  
Camera System ◽  
Physical Size ◽  
System Calibration ◽  
Data Acquisition Card

In order to measure the initial gap between the workpiece and tool-cathode in electrochemical machining, the measurement method based on machine vision was studied in this paper. First, the measurement system based on machine vision was established. The hardware of the system consisted of CCD camera, image data acquisition card, light source and computer. The software of the system was developed by VC++6.0. Then, the original digital image of electrochemical machining initial gap collected by the CCD camera system was changed into the contour of image through graying, bivalency, edge detection and segmentation. Through system calibration, the physical size of the gap was calculated. Finally, relative experiments were carried out. The experimental results validated the feasibility of the method which measures the electrochemical machining initial gap based on machine vision.

scholarly journals Automatic Laser Interferometer And Vision Measurement System For Stripe Rod Calibration

2015 ◽  
Vol 22 (4) ◽  
pp. 491-502 ◽  
Author(s):  
Min Zhao ◽  
Qiu-Hong Huang ◽  
Ling-Jian Zhu ◽  
Zong-Ming Qiu
Keyword(s):  
Measurement System ◽  
Measurement Method ◽  
Laser Interferometer ◽  
Image Data ◽  
Ccd Camera ◽  
Calibration Method ◽  
Feedback Signal ◽  
Long Distance ◽  
Loop Control ◽  
Vision Measurement

Abstract In order to calibrate the stripe precision of a leveling rod, an automatic laser interferometer and a vision measurement system were designed by Xi’an University of Technology in China. The rod was driven by a closed-loop control and the data were collected at the stop state to ensure precision. The laser interferometer provided not only the long distance data but also a position feedback signal in the automatic control loop. CCD camera and a vision measurement method were used to inspect the stripe edge position and defect. A pixel-equivalent self-calibration method was designed to improve precision. ROI (regions of interest) method and an outline tracing method were designed to quickly extract multiple stripe edges. A combination of the image data with the interferometer data reduces control difficulty and ensures the measurement accuracy. The vision measurement method reached sub-pixel precision and the defective edges were reported. The system can automatically calibrate a stripe leveling rod with a high degree of efficiency and precision.

Machine vision-based sensing for helicopter flight control

Robotica ◽  
2000 ◽  
Vol 18 (3) ◽  
pp. 299-303 ◽  
Author(s):  
Carl-Henrik Oertel
Keyword(s):  
Machine Vision ◽  
Measurement System ◽  
Flight Control ◽  
A Priori ◽  
Image Data ◽  
Two Dimensional ◽  
Position Measurement ◽  
Additional Information ◽  
Helicopter Flight ◽  
Template Tracking

Machine vision-based sensing enables automatic hover stabilization of helicopters. The evaluation of image data, which is produced by a camera looking straight to the ground, results in a drift free autonomous on-board position measurement system. No additional information about the appearance of the scenery seen by the camera (e.g. landmarks) is needed. The technique being applied is a combination of the 4D-approach with two dimensional template tracking of a priori unknown features.

Study on the Measuring and Positioning of the Rim Valve Hole Based on Machine Vision

2014 ◽  
Vol 711 ◽  
pp. 333-337 ◽  
Author(s):  
Fang Wang ◽  
Chao Kun Ma ◽  
Shan Qiang Dai ◽  
Chang Chun Li
Keyword(s):  
Image Processing ◽  
Machine Vision ◽  
Measurement Method ◽  
Ccd Camera ◽  
Servo Motor ◽  
Processing Characteristic ◽  
Linear Ccd ◽  
Hole Position ◽  
And Control

The author has designed a visual workbench to realize that the rim can rotate with the workbench. Meanwhile, the linear CCD camera records the rim’s circumference. The paper has explored the measurement method of getting the rim valve hole position using machine vision. The system can calculate the position of rim-hole and control the servo motor by image processing, characteristic recognizing and measuring to locate the position of wheel-hole automatically. And the paper has verified the accuracy of the method by experiments.

How Might Wet Retroreflective Pavement Markings Enable More Robust Machine Vision?

2019 ◽  
Vol 2673 (11) ◽  
pp. 361-366 ◽  
Author(s):  
Adam M. Pike ◽  
Jordan Whitney ◽  
Thomas Hedblom ◽  
Susannah Clear
Keyword(s):  
Machine Vision ◽  
Feature Detection ◽  
Preliminary Investigation ◽  
Image Data ◽  
Ccd Camera ◽  
False Positives ◽  
Lane Detection ◽  
Pavement Markings ◽  
Detection Algorithms ◽  
Night And Day

This study is a preliminary investigation of the effects of levels of wet retroreflectivity of pavement markings on factors that determine robust feature detection in machine vision and light detection and ranging (LiDAR) systems in continuously wet road conditions. Luminance and Weber contrast of a range of pavement markings were characterized as functions of wet retroreflectivity and distance based on calibrated charge-coupled device (CCD) camera measurements. Both were found to trend with wet retroflectivity over the range of distances considered in this study. Artifacts arising from glare sources in wet conditions and their intensities relative to pavement markings of different wet retroreflectivity levels were demonstrated. Image data suggests that markings with high wet retroreflectivity may help to mitigate identification of these artifacts as false positives in lane awareness/lane detection algorithms. As LiDAR presents a viable sensor fusion approach to identifying and avoiding these false positives and artifacts in both nighttime wet and daytime wet road conditions, LiDAR return was characterized on pavement markings comprising both optics designed only for dry retroreflectivity and optics designed to be retroreflective in both dry and wet conditions. Preliminary results suggest that for common pavement marking constructions based on exposed beaded optics that might be completely immersed by a rainstorm or puddling, incorporation of high index (n~2.4) wet retroreflective beaded optics is likely to be advantageous to both visible machine vision systems and LiDAR for detection of those retroreflective markings in both night and day.

Hub Eccentricity Measurement Based on Machine Vision

2013 ◽  
Vol 718-720 ◽  
pp. 409-414 ◽  
Author(s):  
Rui Han ◽  
Feng Ling Zhang ◽  
Shu Xia Guo ◽  
Peng Yin ◽  
Lei Wang
Keyword(s):  
Standard Deviation ◽  
Machine Vision ◽  
Measurement System ◽  
Electrical Discharge Machining ◽  
Ccd Camera ◽  
Maximum Deviation ◽  
Light Illumination ◽  
Image Processing Algorithm ◽  
Rotating Platform ◽  
Bolt Holes

In this investigation, a measurement system based on machine vision applied for auto-hubs eccentricity between the center hole and the pitch circle of bolt holes was proposed. The measurement system was integrated by a CCD camera with a telecentric lens, a diffuse bright-field back light illumination system, a rotating platform, a rotating encoder and an industrial computer. The camera was fixed at a suitable location from the rotation center, which ensured that one bolt hole and a part of the center hole could appear in its visual field. All bolt holes were shot when the auto-hub was rotating, while a rotary encoder recorded these angles. Then a global image of the auto-hub could be tiled by these pictures. An image-processing algorithm integrating morphology, circle fitting, affine transformation and edge extracting was used to measure the auto-hubs eccentricity. According to the measurement of a standard block that had 50um-eccentricity and was manufactured by WEDM-LS (Wire Cut Electrical Discharge Machining-Low Speed), the maximum deviation between measuring value and real value was less than 0.013mm, eccentricitys standard deviation was 0.0035mm and the standard deviation of eccentricitys direction angle was 2.37°. Meanwhile the experimental data of real auto-hubs gave an eccentricitys standard deviation less than 0.013mm and a direction angles standard deviation less than 2.1°.

High-speed brightfield 3-D imaging and 3-D image analysis of thick and overlapped cell clusters in cytological preparations

1994 ◽  
Vol 52 ◽  
pp. 218-219
Author(s):  
Robert W. Mackin
Keyword(s):  
Image Analysis ◽  
High Speed ◽  
Three Dimensional ◽  
Image Data ◽  
Ccd Camera ◽  
Objective Lens ◽  
Array Processor ◽  
Vaginal Smears ◽  
Low Contrast ◽  
Computer Controlled

This paper presents two advances towards the automated three-dimensional (3-D) analysis of thick and heavily-overlapped regions in cytological preparations such as cervical/vaginal smears. First, a high speed 3-D brightfield microscope has been developed, allowing the acquisition of image data at speeds approaching 30 optical slices per second. Second, algorithms have been developed to detect and segment nuclei in spite of the extremely high image variability and low contrast typical of such regions. The analysis of such regions is inherently a 3-D problem that cannot be solved reliably with conventional 2-D imaging and image analysis methods.High-Speed 3-D imaging of the specimen is accomplished by moving the specimen axially relative to the objective lens of a standard microscope (Zeiss) at a speed of 30 steps per second, where the stepsize is adjustable from 0.2 - 5μm. The specimen is mounted on a computer-controlled, piezoelectric microstage (Burleigh PZS-100, 68/μm displacement). At each step, an optical slice is acquired using a CCD camera (SONY XC-11/71 IP, Dalsa CA-D1-0256, and CA-D2-0512 have been used) connected to a 4-node array processor system based on the Intel i860 chip.

scholarly journals Data Augmentation Methods Applying Grayscale Images for Convolutional Neural Networks in Machine Vision

2021 ◽  
Vol 11 (15) ◽  
pp. 6721
Author(s):  
Jinyeong Wang ◽  
Sanghwan Lee
Keyword(s):  
Neural Networks ◽  
Machine Vision ◽  
Object Detection ◽  
Image Classification ◽  
Convolutional Neural Networks ◽  
Data Augmentation ◽  
Image Data ◽  
Manufacturing Productivity ◽  
Smart Factories ◽  
Grayscale Images

In increasing manufacturing productivity with automated surface inspection in smart factories, the demand for machine vision is rising. Recently, convolutional neural networks (CNNs) have demonstrated outstanding performance and solved many problems in the field of computer vision. With that, many machine vision systems adopt CNNs to surface defect inspection. In this study, we developed an effective data augmentation method for grayscale images in CNN-based machine vision with mono cameras. Our method can apply to grayscale industrial images, and we demonstrated outstanding performance in the image classification and the object detection tasks. The main contributions of this study are as follows: (1) We propose a data augmentation method that can be performed when training CNNs with industrial images taken with mono cameras. (2) We demonstrate that image classification or object detection performance is better when training with the industrial image data augmented by the proposed method. Through the proposed method, many machine-vision-related problems using mono cameras can be effectively solved by using CNNs.

Research on Online Measurement Method of Hole Diameter and Position

2013 ◽  
Vol 347-350 ◽  
pp. 197-200
Author(s):  
Yu Gong ◽  
Jing Cai Zhang ◽  
Hong Qi Liu
Keyword(s):  
Comparative Analysis ◽  
Measurement System ◽  
Measurement Method ◽  
Measurement Methods ◽  
Hole Diameter ◽  
Laser Sensor ◽  
Online Measurement ◽  
Online Detection ◽  
Ccd Imaging ◽  
Inductive Sensor

In this paper, research on measurement methods of hole during the parts online detection has been made. Both diameter and position of the hole are going to be detected in the same measurement system. In order to obtain higher accuracy and efficiency, a comparative analysis test of using the contact probes, the inductive sensor, the laser sensor, the forward and back lighting CCD imaging have been achieved. Results show that the contact measurement using inductive sensor is more suitable for the system, for the reason that it has higher reliability and efficiency.

Block Thickness Measurement of Using the Structured Light Vision

2018 ◽  
Vol 33 (01) ◽  
pp. 1955001 ◽  
Author(s):  
Fenghui Lian ◽  
Qingchang Tan ◽  
Siyuan Liu
Keyword(s):  
Machine Vision ◽  
Measurement Method ◽  
Measurement Accuracy ◽  
Thickness Measurement ◽  
Base Plane ◽  
Vision Measurement ◽  
Measurement Results ◽  
Measurement Equations ◽  
Structured Light Vision ◽  
Measuring Base

A method for measuring block thicknesses is proposed by the machine vision measurement. Equations of the measuring base plane and the light plane are formed by calibration. Then, the equation of the light strip image, that is, the image of the intersection between the base plane and light one, is established by the projection relation. Equation of the image of the light strip on the measured plane can be determined by the fitting. Since the light strip on the measuring base plane is parallel to one on the measured plane, the thickness of the measuring block is measured by using the two equations. The experiment evaluates the measurement accuracy of the measurement method and analyzes the influence of some factors on the measurement results.

Accurate measurement method for tube’s endpoints based on machine vision

2016 ◽  
Vol 30 (1) ◽  
pp. 152-163 ◽  
Author(s):  
Shaoli Liu ◽  
Peng Jin ◽  
Jianhua Liu ◽  
Xiao Wang ◽  
Peng Sun
Keyword(s):  
Machine Vision ◽  
Measurement Method
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